---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6581591094216671
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6175
- Accuracy: 0.6582

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0967        | 1.0   | 924  | 1.1282          | 0.6305   |
| 0.9514        | 2.0   | 1848 | 1.0677          | 0.6335   |
| 0.8134        | 3.0   | 2772 | 0.9657          | 0.6761   |
| 0.5172        | 4.0   | 3696 | 1.0638          | 0.6641   |
| 0.4644        | 5.0   | 4620 | 1.1745          | 0.6655   |
| 0.3079        | 6.0   | 5544 | 1.2914          | 0.6601   |
| 0.1569        | 7.0   | 6468 | 1.4210          | 0.6636   |
| 0.1324        | 8.0   | 7392 | 1.5083          | 0.6603   |
| 0.0833        | 9.0   | 8316 | 1.5875          | 0.6644   |
| 0.1019        | 10.0  | 9240 | 1.6175          | 0.6582   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1